Physicians face significant difficulties retrieving essential patient information from existing medical data entry systems. These difficulties divert clinicians' time away from direct patient care, with essential patient information sometimes remaining undiscovered. Concept-centered, time- oriented medical data organization should improve physicians' efficiency in gathering essential data from medical records. It is likely that improved efficiency in data retrieval should favorably affect processes of care, physician satisfaction, and patient satisfaction. To test these hypotheses, this study will extend previous work on oncology multi-media databases to create a software system, called TimeLine, which presents clinical data using a domain-specific ontology and an adjustable temporal granularity. TimeLine will undergo technical assessments first using traditional information retrieval measures. Thereafter, TimeLine will be deployed in two clinical settings using time-series designs. The technical objectives of the project will address concept characterization and data retrieval in the domain of pulmonary diseases. A domain-specific knowledge base will be developed that models data according to high level abstractions of organ system, medical condition, symptom, or other concept. The computer interface will be designed for various physician profiles, but will be capable of adapting to varying requirements of temporal abstraction and depth of detail, depending upon the information needs of the physician. Implementation of the system will use World Wide Web technology. System evaluation will proceed in three parts. The accuracy of automated data pre-fetching as well as data organization at incremental levels of abstraction (organ system, problem, etc.) will be assessed using the classical measures of precision and recall. After final refinements have been made to the interface, the influence of TimeLine on processes of care and physician satisfaction will be compared to existing data information environments in real clinical settings using a time-series "off- on-off" trial design in which pulmonologists use traditional, than TimeLine, then traditional data environments in the course of responding to consultations on hospitalized patients. Using information from billing records, medical records reviews, and time-motion studies, each patient's time to clinical stabilization, and resource utilization will be measured as process variables. Physician satisfaction will be assessed using standardized instruments. Finally, using a similar time-series trial design in UCLA Thoracic Oncology Clinic, oncologic radiologists' and oncologists' satisfaction with the data environment will be measured. Patient quality of life measures will also be explored in the respective data environments. This will be the first study to link a detailed conceptual model and interface with measures of essential information retrieval and to determine the value of an improved information environment in healthcare processes.